topicmodels: Topic Models

Provides an interface to the C code for Latent Dirichlet Allocation (LDA) models and Correlated Topics Models (CTM) by David M. Blei and co-authors and the C++ code for fitting LDA models using Gibbs sampling by Xuan-Hieu Phan and co-authors.

Version: 0.2-5
Depends: R (≥ 2.15.0)
Imports: stats4, methods, modeltools, slam, tm (≥ 0.6)
Suggests: lasso2, lattice, lda, OAIHarvester, SnowballC, XML, corpus.JSS.papers
Published: 2017-02-28
Author: Bettina Grün [aut, cre], Kurt Hornik [aut]
Maintainer: Bettina Grün <Bettina.Gruen at>
License: GPL-2
NeedsCompilation: yes
SystemRequirements: GNU Scientific Library version >= 1.8, C++11
Citation: topicmodels citation info
Materials: NEWS
In views: NaturalLanguageProcessing
CRAN checks: topicmodels results


Reference manual: topicmodels.pdf
Vignettes: topicmodels: An R Package for Fitting Topic Models
Package source: topicmodels_0.2-5.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X Mavericks binaries: r-release: topicmodels_0.2-5.tgz, r-oldrel: topicmodels_0.2-5.tgz
Old sources: topicmodels archive

Reverse dependencies:

Reverse imports: ldatuning, preText, textmineR, textmining
Reverse suggests: LDAvis, PivotalR, quanteda, tidytext


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